Macias Michal, Sierociuk Dominik, Malesza Wiktor
Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland.
Sensors (Basel). 2022 Jan 11;22(2):527. doi: 10.3390/s22020527.
This paper is devoted to identifying parameters of fractional order noises with application to noises obtained from MEMS accelerometer. The analysis and parameters estimation will be based on the Triple Estimation algorithm, which can simultaneously estimate state, fractional order, and parameter estimates. The capability of the Triple Estimation algorithm to fractional noises estimation will be confirmed by the sets of numerical analyses for fractional constant and variable order systems with Gaussian noise input signal. For experimental data analysis, the MEMS sensor SparkFun MPU9250 Inertial Measurement Unit (IMU) was used with data obtained from the accelerometer in , and -axes. The experimental results clearly show the existence of fractional noise in this MEMS' noise, which can be essential information in the design of filtering algorithms, for example, in inertial navigation.
本文致力于识别分数阶噪声的参数,并将其应用于从MEMS加速度计获得的噪声。分析和参数估计将基于三重估计算法,该算法可以同时估计状态、分数阶和参数估计值。对于具有高斯噪声输入信号的分数常数和可变阶系统,通过数值分析集将证实三重估计算法对分数噪声估计的能力。对于实验数据分析,使用了MEMS传感器SparkFun MPU9250惯性测量单元(IMU),并从加速度计在x、y和z轴上获得数据。实验结果清楚地表明,该MEMS噪声中存在分数阶噪声,这在例如惯性导航的滤波算法设计中可能是至关重要的信息。